QUANTILE_TDIGEST_WEIGHTED
import FunctionDescription from '@site/src/components/FunctionDescription';
Computes an approximate quantile of a numeric data sequence using the t-digest algorithm. This function takes into account the weight of each sequence member. Memory consumption is log(n), where n is a number of values.
Caution: NULL values are not included in the calculation.
Analyze Syntax
func.quantile_tdigest_weighted(<levels>, <expr>, <weight_expr>)
Analyze Examples
func.quantile_tdigest_weighted([0.5, 0.8], table.sales_amount, 1).alias('sales_amounts')
| sales_amounts |
|-----------------------+
| [6000.0,7000.0] |
SQL Syntax
QUANTILE_TDIGEST_WEIGHTED(<level1>[, <level2>, ...])(<expr>, <weight_expr>)
Arguments
Arguments | Description |
---|---|
<level n> | A level of quantile represents a constant floating-point number ranging from 0 to 1. It is recommended to use a level value in the range of [0.01, 0.99]. |
<expr> | Any numerical expression |
<weight_expr> | Any unsigned integer expression. Weight is a number of value occurrences. |
Return Type
Returns either a Float64 value or an array of Float64 values, depending on the number of quantile levels specified.
SQL Examples
-- Create a table and insert sample data
CREATE TABLE sales_data (
id INT,
sales_person_id INT,
sales_amount FLOAT
);
INSERT INTO sales_data (id, sales_person_id, sales_amount)
VALUES (1, 1, 5000),
(2, 2, 5500),
(3, 3, 6000),
(4, 4, 6500),
(5, 5, 7000);
SELECT QUANTILE_TDIGEST_WEIGHTED(0.5)(sales_amount, 1) AS median_sales_amount
FROM sales_data;
median_sales_amount|
-------------------+
6000.0|
SELECT QUANTILE_TDIGEST_WEIGHTED(0.5, 0.8)(sales_amount, 1)
FROM sales_data;
quantile_tdigest_weighted(0.5, 0.8)(sales_amount)|
-------------------------------------------------+
[6000.0,7000.0] |
Last modified June 11, 2024 at 9:00 PM EST: clean up cautions and notes (d4a1b9a)